Data Engineering Manager, Growth & Revenue
openai
Job Score
100 ptsAbout the Team
The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI.
About the Role
We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement.
In this role, you will:
Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas.
Define the data strategy for all the data subject areas you own.
Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue.
Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions.
Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics.
Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems.
Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response.
Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders.
You might thrive in this role if you:
Have deep experience leading and scaling data engineering teams in a fast-moving product or technology environment.
Bring strong technical judgment across modern data systems, including SQL, Python or Scala, Spark, orchestration, dimensional and event modeling, and lakehouse or warehouse architectures.
Have built trusted growth, lifecycle, attribution, subscription, billing, payments, revenue, or monetization data products at meaningful scale.
Can turn ambiguous business questions into durable data contracts, metric definitions, and technical roadmaps.
Build unusually strong partnerships with Data Science, Product, Finance, Financial Engineering, GTM, and Engineering.
Care deeply about data quality, privacy, security, and the operational health of systems used for consequential decisions.
Are an excellent people leader: you hire well, develop talent, give clear feedback, and create an environment where diverse perspectives do their best work.
What success looks like
In the first 90 days, you have earned trust with the team and partners, clarified ownership boundaries, assessed the current data portfolio, and aligned on a prioritized roadmap.
Within a year, Growth & Revenue stakeholders rely on a smaller set of trustworthy, well-owned datasets and metrics for lifecycle, attribution, subscriber, billing, payment, monetization, and revenue decisions.
The team operates with clear goals, healthy execution rhythms, strong reliability standards, and a hiring and development plan that matches the domain’s ambition.
This role is based in our San Francisco headquarters. We offer relocation assistance for new employees.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About Data
The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.
Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.
The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.
About Engineering
Software Engineering goes beyond traditional development, focusing on scalability, performance, and system architecture. Software engineers are responsible for designing infrastructures that support millions of simultaneous users.
Skills include microservices architecture, DevOps, cloud computing, application security, and performance optimization. Knowledge of containerization (Docker, Kubernetes) and CI/CD is increasingly required.
Senior software engineers are rare and highly compensated professionals, with opportunities at major global tech companies.
About Business Intelligence
Business Intelligence (BI) is the area responsible for transforming raw data into strategic information for decision-making. BI professionals build dashboards, reports, and analyses that help companies understand their performance and identify growth opportunities.
Key skills include data modeling (star schema, snowflake), ETL (extraction, transformation, loading), advanced SQL, BI tools (Power BI, Tableau, Looker), data warehousing, KPIs, and business metrics analysis (MRR, churn, cohort). Knowledge of dbt, Airflow, and data pipelines is a differentiator.
BI professionals in technology companies are highly valued, especially those who master data visualization, analytics engineering, and can translate complex data into actionable insights for the business. The field offers opportunities from BI analyst to head of data, with a focus on data-driven decision making.
Discover Other Areas
Understand the scope of work, key skills, and tools used in different career areas.
About Marketing
The Marketing area is strategic for the growth and positioning of any company. It encompasses traditional marketing, brand management, market research, trade marketing, product marketing, and market intelligence. Marketing professionals are responsible for planning and executing strategies that connect brands to their target audience.
Key skills include brand management, market research, competitive analysis, product marketing, trade marketing, pricing, relationship marketing, and channel development. Knowledge of research tools (Nielsen, Kantar, Ipsos), BI, and advanced spreadsheets is a differentiator.
Marketing professionals in technology companies are highly valued, especially those who master product marketing, go-to-market strategy, and data-driven marketing. The field offers opportunities from analyst to CMO, with a focus on growth, brand positioning, and return on investment.
About Systems Analyst
The Systems Analyst is the professional responsible for analyzing, designing, and implementing technology solutions that meet business needs. They act as a bridge between business areas and the development team, ensuring that systems deliver real value to the organization.
Key skills include requirements gathering and analysis, process modeling (BPMN), data modeling, technical and functional documentation, system integration (APIs, microservices), and knowledge of ERPs and CRMs. Tools like Jira, Confluence, Visio, and project management platforms are essential.
Systems Analysts in technology companies are highly valued, especially those who master agile requirements analysis (user stories, backlog), system integration, and solution architecture. The field offers opportunities from junior analyst to solution architect, with a focus on efficiency, quality, and technological innovation.
About Web3
The Web3 area represents the new phase of the decentralized internet, built on blockchain technology. Web3 professionals create decentralized applications (dApps), interact with smart contracts, manage digital assets (cryptocurrencies and NFTs), and utilize DeFi (Decentralized Finance) protocols, revolutionizing how data, ownership, and finance are managed online.
About Content Writer
The Content Writer is the professional responsible for creating quality written content for websites, blogs, social media, and other digital platforms. They combine writing skills with content strategy and SEO to attract, engage, and convert audiences.
Key skills include blog content creation, landing pages, newsletters, social media content, keyword research, content strategy, editorial calendar, and SEO writing. Knowledge of WordPress, Surfer SEO, Ahrefs, and analytics tools is a differentiator.
Content Writers in technology companies are highly valued, especially those who can create accessible technical content, evergreen content, and content that generates organic traffic. The field offers opportunities from junior content writer to head of content, with a focus on quality, strategy, and content performance.
About Technical Support
Technical Support is essential to ensure customer satisfaction and retention. Support professionals resolve technical issues, document solutions, and identify patterns that can lead to product improvements.
Key skills include troubleshooting, customer service, technical documentation, ITIL knowledge, and ticketing tools (Zendesk, Freshdesk, Intercom).
Technical support has evolved from a reactive to a proactive function, with high-level professionals working in Customer Engineering and Support Engineering.
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